make_split_overlays.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib,aplpy,numpy,glob\n",
    "from astropy.wcs import WCS\n",
    "from astropy.io import fits\n",
    "from astropy.table import Table\n",
    "from astropy.table import QTable\n",
    "import matplotlib.pyplot as plt\n",
    "import common_functions as cf\n",
    "from astropy import units\n",
    "from astropy.coordinates import SkyCoord\n",
    "import aplpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "font = {'size'   : 14, 'family' : 'serif', 'serif' : 'cm'}\n",
    "plt.rc('font', **font)\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['lines.linewidth'] = 1\n",
    "plt.rcParams['axes.linewidth'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "contour_scheme = numpy.array([1.,2.,4.,8.,16.,32.,64.])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "GBT_point = QTable([[92, 48, 58, 88, 91, 37, 68, 79, 93, 7, 16, 25, 31, 97, 23, 30, 100, 15, 26, 10, 33, 90, 40],\n",
    "                    ['22h35m57.500s','10h37m45.600s','11h42m10.700s','20h52m24.000s','22h09m10.400s','09h13m35.600s','13h53m26.000s','15h59m11.800s','23h15m24.200s',\n",
    "                     '00h39m23.900s','02h09m31.300s','03h20m43.700s','05h01m38.300s','23h47m22.900s','03h07m06.400s','04h36m28.600s','00h01m20.700s','02h07m38.900s',\n",
    "                     '03h21m54.200s','01h26m13.000s','05h10m47.900s','22h02m05.600s','09h38m54.500s'],\n",
    "                    ['+33d57m35.00s','-27d04m49.00s','+10d18m21.00s','-05d45m00.00s','-27d47m45.00s','+30d00m51.00s','+40d19m08.00s','+20d45m30.00s','+18d58m59.00s',\n",
    "                     '+00d52m41.00s','-10d09m30.00s','-01d03m06.00s','-04d15m25.00s','-02d19m34.00s','-09d35m07.00s','-02d49m56.00s','+13d07m57.00s','+02d08m17.00s',\n",
    "                     '-13d38m45.00s','+34d42m41.00s','+18d02m05.00s','-31d58m00.00s','-04d51m07.00s']],\n",
    "                   names = ['HCG', 'ra', 'dec'])\n",
    "GBT_point.add_index('HCG')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCGs = Table.read('tables/HCGs.vo', format='votable')\n",
    "HCGs.add_index('HCG')\n",
    "\n",
    "HCG_mems = Table.read('tables/HCG_members.vo', format='votable')\n",
    "\n",
    "HCGs['logMHI_gals'] = numpy.zeros(len(HCGs))+numpy.nan\n",
    "HCGs['logMHI_exfs'] = numpy.zeros(len(HCGs))+numpy.nan\n",
    "\n",
    "HCG_mems['logMHI'] = numpy.zeros(len(HCG_mems))+numpy.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_overlay(HCG, ra_cen, dec_cen, width, dist, mem_offsets=None, opt_survey='DECaLS'):\n",
    "    \n",
    "    fits_file_list = glob.glob(f'SoFiA_masks/HCG{HCG}/separated_features/*.fits')\n",
    "    src_cat = 'SoFiA_masks/HCG{0}/HCG{0}_cat.xml'.format(HCG)\n",
    "    sofia_mom0 = 'SoFiA_masks/HCG{0}/HCG{0}_mom0.fits'.format(HCG)\n",
    "    pbcube = 'SoFiA_masks/HCG{0}/HCG{0}_HI.pbcor.fits'.format(HCG)\n",
    "    if 'POSS' in opt_survey:\n",
    "        optical_image = opt_survey+'_images/HCG{0}_R.fits'.format(HCG)\n",
    "    else:\n",
    "        optical_image = opt_survey+'_images/r_fits/HCG{0}_r.fits'.format(HCG)\n",
    "        \n",
    "    members = list(HCG_mems['name'][HCG_mems['HCG'] == HCG])\n",
    "    src_cat = Table.read(src_cat)\n",
    "    rms = numpy.mean(src_cat['rms'])\n",
    "    \n",
    "    mem_ras = list(HCG_mems[HCG_mems['HCG'] == HCG]['ra'])\n",
    "    mem_decs = list(HCG_mems[HCG_mems['HCG'] == HCG]['dec'])\n",
    "    mem_labels = list(HCG_mems[HCG_mems['HCG'] == HCG]['m_HCG'])\n",
    "    for i,name in enumerate(mem_labels):\n",
    "        if name == '':\n",
    "            mem_labels[i] = HCG_mems[HCG_mems['HCG'] == HCG]['name'][i]\n",
    "        else:\n",
    "            mem_labels[i] = mem_labels[i].upper()\n",
    "            \n",
    "    for i,name in enumerate(mem_labels):\n",
    "        if len(name) == 4+len(str(HCG)):\n",
    "            if name[:-1] == f'HCG{HCG}':\n",
    "                mem_labels[i] = mem_labels[i][-1:].upper()\n",
    "            \n",
    "    \n",
    "    if mem_offsets is None:\n",
    "        mem_offsets = numpy.zeros((len(mem_ras),2))\n",
    "\n",
    "    for pb_cubelet in fits_file_list:\n",
    "\n",
    "        cube,cube_ra,cube_dec,cube_vel,bmaj,bmin,pa,beam_factor,cube_dx,cube_dy,cube_dv = cf.read_fitscube(pb_cubelet,True,True)\n",
    "        \n",
    "        n_HI = (rms*abs(cube_dv)*4.*numpy.log(2.)*2.356E-7)/(numpy.pi*bmaj*bmin*(numpy.pi/(180.*3600.))**2.)\n",
    "        N_HI = n_HI*cf.Msol/(cf.mp*(cf.pc*10.)**2.)\n",
    "\n",
    "        #Catch the error that SlicerAstro sometimes writes an incorrect value in pixel (0,0,0)\n",
    "        if abs(cube[0,0,0]) > 1.:\n",
    "            cube[0,0,0] = 0.\n",
    "\n",
    "        mom0 = numpy.nansum(cube,axis=0)*abs(cube_dv)\n",
    "\n",
    "        if 'mem_mom0' not in locals():\n",
    "            mem_mom0 = numpy.zeros(numpy.shape(mom0))\n",
    "            non_mom0 = numpy.zeros(numpy.shape(mom0))\n",
    "            tid_mom0 = numpy.zeros(numpy.shape(mom0))\n",
    "        \n",
    "        if numpy.shape(mom0) != numpy.shape(mem_mom0):\n",
    "            print('ERROR: Cubelets not all the same dimensions.')\n",
    "            return None\n",
    "            \n",
    "        #Identify what object is classified as\n",
    "        group_feature = False\n",
    "        feat_code = ['br','ex','tl','cl']\n",
    "        for feature in feat_code:\n",
    "            if feature in pb_cubelet:\n",
    "                inx = pb_cubelet.index(feature)\n",
    "                print(f'HCG{HCG}'+pb_cubelet[inx:inx+len(feature)+1]+' is a non-galactic feature.')\n",
    "                group_feature = True\n",
    "                break\n",
    "\n",
    "        group_member = False\n",
    "        if not group_feature:\n",
    "            for mem in members:\n",
    "                if mem+'.fits' in pb_cubelet:\n",
    "                    print(f'{mem} is a member of HCG{HCG}.')\n",
    "                    group_member = True\n",
    "                    break\n",
    "\n",
    "        #Add exceptions for HCGs 47, 49, 57, and 100\n",
    "        if (\"abcd\" in pb_cubelet) or (\"acd\" in pb_cubelet) or (\"ab\" in pb_cubelet):\n",
    "            group_member = True\n",
    "            inx1 = pb_cubelet.index('features/')+9\n",
    "            inx2 = pb_cubelet.index('.fits')\n",
    "            print(pb_cubelet[inx1:inx2]+f' is part of HCG{HCG}.')\n",
    "            \n",
    "        if group_member:\n",
    "            mem_mom0 += mom0\n",
    "        elif group_feature:\n",
    "            tid_mom0 += mom0\n",
    "        else:\n",
    "            non_mom0 += mom0\n",
    "    \n",
    "    hdu = fits.open(fits_file_list[0])\n",
    "    wcs = WCS(hdu[0].header,naxis=2)\n",
    "    \n",
    "\n",
    "    cen_pos = [ra_cen,dec_cen]\n",
    "    fig_wid = width\n",
    "    \n",
    "    min_contour = 4.*rms*abs(cube_dv)*numpy.sqrt(20./abs(cube_dv))\n",
    "    print(min_contour)\n",
    "    \n",
    "    #Initialise figure\n",
    "    f = aplpy.FITSFigure(optical_image, figsize=(8.,8.), dimensions=[0, 1])\n",
    "\n",
    "    #Re-centre and set size (identical to above command)\n",
    "    f.recenter(cen_pos[0], cen_pos[1], radius=fig_wid/2.)\n",
    "\n",
    "    #Overlay contours\n",
    "    hdu = fits.PrimaryHDU(mem_mom0)\n",
    "    hdu.header.update(wcs.to_header())\n",
    "    f.show_contour(hdu,colors=['blue'],\n",
    "                         levels=[-1.*min_contour],linestyle='--')\n",
    "    f.show_contour(hdu,colors=['blue'],\n",
    "                         levels=min_contour*contour_scheme)\n",
    "    hdu = fits.PrimaryHDU(tid_mom0)\n",
    "    hdu.header.update(wcs.to_header())\n",
    "    f.show_contour(hdu,colors=['green'],\n",
    "                         levels=[-1.*min_contour],linestyle='--')\n",
    "    f.show_contour(hdu,colors=['green'],\n",
    "                         levels=min_contour*contour_scheme)\n",
    "    hdu = fits.PrimaryHDU(non_mom0)\n",
    "    hdu.header.update(wcs.to_header())\n",
    "    f.show_contour(hdu,colors=['red'],\n",
    "                         levels=[-1.*min_contour],linestyle='--')\n",
    "    f.show_contour(hdu,colors=['red'],\n",
    "                         levels=min_contour*contour_scheme)\n",
    "    #Contour values in Jy km/s per beam\n",
    "\n",
    "    #Display r-band image\n",
    "    if 'POSS' not in opt_survey:\n",
    "        f.show_colorscale(cmap='Greys',vmin=1E-4,vmax=2.5,stretch='log')\n",
    "    else:\n",
    "        f.show_colorscale(cmap='Greys',pmin=0.1,pmax=99.8,stretch='log')\n",
    "        \n",
    "    if HCG in GBT_point['HCG']:\n",
    "        print('GBT')\n",
    "        GBT_pointing = SkyCoord(GBT_point.loc[HCG]['ra'], GBT_point.loc[HCG]['dec'], frame='icrs', equinox='J2000')\n",
    "        f.show_circles(xw=GBT_pointing.ra.deg,yw=GBT_pointing.dec.deg,radius=9.1/120.,edgecolor='orange', lw=3, ls='dotted')\n",
    "\n",
    "    #Add beam\n",
    "    hdu = fits.open(pbcube)\n",
    "    f.show_ellipses(xw=cen_pos[0]+0.4*fig_wid/numpy.cos(cen_pos[1]*numpy.pi/180.), yw=cen_pos[1]-0.4*fig_wid, \n",
    "                    width=hdu[0].header['BMIN'], height=hdu[0].header['BMAJ'], angle=hdu[0].header['BPA'], \n",
    "                    facecolor='k', lw=0)\n",
    "\n",
    "    #Label galaxies\n",
    "    for i in range(len(mem_ras)):\n",
    "        f.add_label(mem_ras[i]+mem_offsets[i][0],mem_decs[i]+mem_offsets[i][1],mem_labels[i],c='k',weight='bold')\n",
    "\n",
    "    #Add scalebar\n",
    "    f.add_scalebar((180./numpy.pi)*0.02/dist, corner='bottom right', lw=4, label=\"20 kpc\")\n",
    "    \n",
    "    #Title\n",
    "    f.set_title(f'HCG {HCG}')\n",
    "        \n",
    "    f.savefig('overlays/HCG{}_split_overlay.pdf'.format(HCG),dpi=100)\n",
    "    f.savefig('overlays/HCG{}_split_overlay.png'.format(HCG),dpi=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 2\n",
    "split_overlay(HCG, 7.8593, 8.4384, 0.2, HCGs.loc[HCG]['dist'], mem_offsets = [[0.008,0.],[0.,-0.012],[0.008,0.]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 7\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.2, HCGs.loc[HCG]['dist'], \n",
    "              mem_offsets = [[-0.015,-0.005],[0.012,0.005],[-0.02,-0.02],[0.01,-0.01]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 10\n",
    "split_overlay(HCG, 21.5277, 34.7159, 0.25, HCGs.loc[HCG]['dist'], opt_survey='SDSS', \n",
    "              mem_offsets = [[0.,-0.02],[-0.005,0.005],[-0.015,0.],[0.025,0.015]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 15\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.2, HCGs.loc[HCG]['dist'], \n",
    "              mem_offsets = [[-0.012,0.012],[0.012,-0.012],[0.012,-0.012],\n",
    "                             [-0.012,-0.012],[0.,-0.01],[0.002,0.012]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 16\n",
    "split_overlay(HCG, 32.4251, -10.2207, 0.35, HCGs.loc[HCG]['dist'], \n",
    "              mem_offsets = [[-0.04,-0.016],[-0.015,-0.005],[0.03,0.0],\n",
    "                             [-0.02,-0.02],[0.015,-0.005]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 19\n",
    "split_overlay(HCG, 40.6731, -12.4158, 0.3, HCGs.loc[HCG]['dist'], \n",
    "              mem_offsets = [[-0.015,0.015],[0.015,0.],[-0.015,0.015]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 22\n",
    "split_overlay(HCG, 45.8892, -15.5835, 0.25, HCGs.loc[HCG]['dist'], \n",
    "              mem_offsets = [[-0.02,0.03],[-0.015,0.],[0.02,0.02],[-0.035,0.]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 23\n",
    "split_overlay(HCG, 46.7789, -9.5633, 0.2, HCGs.loc[HCG]['dist'], \n",
    "              mem_offsets = [[-0.02,0.015],[-0.006,0.005],[0.015,0.],[-0.03,0.],[0.005,-0.005]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 25\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.25, HCGs.loc[HCG]['dist'], \n",
    "              mem_offsets = [[0.025,0.0],[0.005,0.01],[-0.007,0.005],[-0.01,0.]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 26\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.125, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.002,-0.002],[0.0,0.004],[0.0,-0.002],[0.002,-0.002],\n",
    "                           [0.002,0.002],[0.002,-0.002],[-0.005,0.002]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 30\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.25, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.007,0.007],[-0.015,0.015],[0.0,-0.009],[-0.01,0.01]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 31\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.125, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.008,0.0],[0.008,0.0],[-0.003,0.003],[-0.003,0.003],[0.003,0.0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 33\n",
    "split_overlay(HCG, 77.7031, 18.0259, 0.08, HCGs.loc[HCG]['dist'], opt_survey='POSS',\n",
    "              mem_offsets=[[0.001,0.0],[0.002,0.002],[0.001,-0.001],[-0.003,0.003]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 37\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.2, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.005,0.005],[0.006,0.0],[-0.006,0.003],[0.0,-0.006],[0.01,0.00]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 40\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.2, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.00,0.005],[-0.003,-0.005],[0.0,-0.007],[-0.01,0.003],[0.007,0.00]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 47\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.1, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.00,0.004],[-0.008,0.0],[0.005,0.0],[-0.006,0.0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 48\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.2, HCGs.loc[HCG]['dist'], opt_survey='POSS',\n",
    "              mem_offsets=[[-0.01,0.00],[0.007,0.007]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 49\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.1, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.003,0.003],[0.003,-0.003],[-0.003,0.003],[-0.04,0.0],[-0.003,0.003]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 54\n",
    "split_overlay(HCG, 172.3136, 20.5827, 0.15, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.025,0.005],[numpy.nan,numpy.nan],[numpy.nan,numpy.nan],\n",
    "                           [numpy.nan,numpy.nan],[numpy.nan,numpy.nan]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 56\n",
    "split_overlay(HCG, 173.1638, 52.9428, 0.1, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.004,0.004],[0.001,-0.004],[-0.003,0.003],\n",
    "                           [-0.003,0.003],[0.015,0.00]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 57\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.15, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.008,0.00],[0.00,0.007],[0.005,0.00],[0.005,0.005],\n",
    "                           [0.003,0.005],[-0.01,0.0],[-0.01,0.0],[0.002,-0.005]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 58\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.25, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.01,0.00],[0.02,0.0],[-0.01,0.01],\n",
    "                           [-0.015,0.0],[0.01,0.0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 59\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec']-0.01, 0.1, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.005,0.005],[0.001,0.005],[0.0,0.007],[0.007,0.005]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 61\n",
    "split_overlay(HCG, 183.1047, 29.1806, 0.275, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.01,-0.01],[0.012,0.01],[0.004,-0.01]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 68\n",
    "split_overlay(HCG, 208.3808, 40.3327, 0.25, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.01,0.01],[0.015,0.0],[-0.01,-0.01],\n",
    "                           [0.015,0.0],[-0.015,0.015]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 71\n",
    "split_overlay(HCG, 212.7489, 25.5204, 0.15, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.007,-0.002],[-0.005,0.0],[-0.03,0.005],\n",
    "                           [0.0,0.01],[-0.008,0.008]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 79\n",
    "split_overlay(HCG, 239.8006, 20.7571, 0.075, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.003,0.002],[-0.003,-0.001],[-0.003,0.001],[0.0,0.002]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 88\n",
    "split_overlay(HCG, 313.0990, -5.7520, 0.2, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.008,0.008],[0.015,-0.005],[-0.017,0.0],[-0.008,0.008]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 90\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.3, HCGs.loc[HCG]['dist'], opt_survey='POSS',\n",
    "              mem_offsets=[[0.0,-0.01],[0.01,0.0],[0.015,0.025],[-0.015,0.0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 91\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.2, HCGs.loc[HCG]['dist'], opt_survey='POSS',\n",
    "              mem_offsets=[[-0.015,0.0],[0.01,0.0],[0.01,0.0],[-0.005,0.005]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 92\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.125, HCGs.loc[HCG]['dist'], opt_survey='SDSS',\n",
    "              mem_offsets=[[-0.007,0.0],[0.0,0.005],[-0.004,-0.004],[0.007,0.0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 93\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.25, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.015,-0.015],[-0.015,0.00],[0.01,0.01],[-0.025,0.0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 96\n",
    "split_overlay(HCG, HCGs.loc[HCG]['ra'], HCGs.loc[HCG]['dec'], 0.25, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[-0.01,0.01],[0.0,0.01],[0.01,-0.01],[0.00,-0.01]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 97\n",
    "split_overlay(HCG, 356.8423, -2.3279, 0.25, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.01,0.005],[-0.005,-0.005],[-0.005,0.005],\n",
    "                           [-0.015,0.0],[0.00,0.01]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "HCG = 100\n",
    "split_overlay(HCG, 0.3409, 13.1206, 0.25, HCGs.loc[HCG]['dist'],\n",
    "              mem_offsets=[[0.0,0.015],[0.008,0.008],[-0.01,0.0],[-0.005,0.005],[-0.003,0.01]])"
   ]
  }
 ],
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